1. Field of the Invention
The present invention relates to a calculation method and apparatus of an index concerning local blood flow circulations in cerebral tissues.
2. Description of the Related Art
In X-ray CT inspection, configuration information from a simple CT image, and circulation information of blood flow around a seat of disease in a dynamic scan by contrast CT can be obtained as visual information. In recent years, a high-speed scan by multislice CT has been possible and it is considered that a utilization range of the dynamic scan of contrast CT is increasingly enlarged.
As one directionality, there is a method called a CBP study for calculating an index concerning blood flow circulations of capillaries in cerebral tissues. The CBP study comprises: obtaining indices such as CBP, CBV, MTT, and Err quantitatively indicating local blood flow circulations in the tissues, that is, the circulations of the blood flow through the capillaries in the local tissues; and outputting maps of these indices.
CBP denotes blood flow rate [ml/100 ml/min] per unit volume and time in the capillaries for the cerebral tissues; CBV denotes a blood volume [ml/100 ml] per unit volume in the cerebral tissues; MTT denotes a blood mean transit time [second] of the capillaries; and Err denotes a sum of residual errors or square root of the sum of squares of the residual errors in approximation of a modulation transfer function.
The indices CBP, CBV, MTT quantitatively indicating the blood flow circulations of the capillaries in the cerebral tissues, together with transit time information after development of cerebral ischemia apoplexy, are expected as useful information for differentiating a disease body of ischemic cerebral vascular disorder, judging the presence/absence of enlargement of the capillaries, or evaluating blood flow rate. For example, in general, in ischemic cerebral vascular disorders, blood pressure of a provided artery drops, and the intravascular blood flow rate drops. As a result, even when the CBV is constant, MTT extends, and CBP drops. Moreover, in a cerebral infarction hyperacute stage, to compensate for the drop of the blood flow rate by the blood pressure drop, there is an autoregulation for expanding the capillaries, increasing the blood flow rate CBP. Therefore, since the MTT extends, even with the drop of the CBP, with the increase of the CBV, the information implies a possibility of revascularization of the capillaries.
In the CBP study, a contrast medium having no cerebral vessel permeability, such as an iodinated contrast medium, is used as a tracer. The iodinated contrast medium is injected via a cubital vein, for example, by an injector. The iodinated contrast medium injected into the vein by the injector flows into a cerebral artery via heart and lung. Then, the contrast medium flows out to the cerebral veins from the cerebral arteries through the capillaries in the cerebral tissues. The iodinated contrast medium passes through the capillaries in normal cerebral tissues without any extravascular leakage. FIG. 1 schematically shows this state.
The state of passage of the contrast medium is scanned by dynamic CT, and a time-density curve Ca(t) of a pixel on the cerebral artery, time-density curve Ci(t) of the pixel on the cerebral tissue (capillary), and time-density curve Csss(t) of the pixel on the cerebral vein are measured from a continuous image.
Here, in the CBP study, an ideal relation established between the time-density curve Ca(t) of the cerebral artery and the time-density curve Ci(t) of the cerebral tissue is used as an analysis model. Assuming if the contrast medium is injected via the vessel immediately before the cerebral tissue, the time-density curve in the unit volume (one pixel) for the cerebral tissue rides vertically, holds a constant value for a while, and thereafter falls steeply. This is approximated with a rectangular function (box-modulation transfer function method: box-MTF method).
That is, the time-density curve Ca(t) of the cerebral artery is used as an input function, the time-density curve Ci(t) for the cerebral tissue is used as an output function, and a modulation transfer function between the input and output functions is approximated by a rectangular function. The modulation transfer function indicates a process of passage of the tracer through the capillary.
The CBP study has the following problems.
Since the respective indices of the CBP, CBV, MTT, and Err are calculated for each pixel (x,y,z), an image using the value as the pixel value can be constituted, and this image is referred to as a map. For example, when R types of indices are obtained, R maps can be constituted. The R maps prepared in this manner can be regarded as one map (vector value map) in which each pixel has a vector value. That is, the map can be represented as follows.Vk(x,y,z)=<Pk,1(x,y,z), Pk,2(x,y,z), . . . , Pk,R(x,y,z)>
For example, the CBP study can be constituted in such a manner that typically R=4 is assumed, Pk,1(x,y,z) indicates the value of CBP, Pk,2(x,y,z) indicates the value of CBV, Pk,3(x,y,z) indicates the value of MTT, and Pk,4(x,y,z) indicates the value of a residual errors error Err.
This vector value map Vk is prepared for each time-density curve Ca(t)k of the referred cerebral artery. For example, assuming that the time-density curves of the cerebral arteries are obtained from medial, anterior and posterior cerebral arteries in left and right hemispheres. In this case, K=6. Furthermore, assuming that the time-density curve of the cerebral artery is obtained from artery several portions in the periphery of an affected area, K=about 10 to 15.
When the number K of the time-density curve Ca(t)k of the cerebral artery is large (k=1, 2, . . . , K), the number of vector value maps Vk (k=1, 2, . . . , K) obtained as a result is large, and this is therefore inconvenient for observation. That is, when the map is to be observed as a usual gray scale image or color scale image, one map is constituted of R images, there are K maps, and therefore K×R images in total have to be compared. Furthermore, the area nourished by an artery and the artery are not necessarily apparent, and an anatomical knowledge is necessary to judge the map Vk (k=1, 2, . . . , K) to be observed for each area. Particularly, in the development of the cerebral vascular disorder such as the cerebral infarction, the judgment of the artery which depends on the tissue may not agree with the anatomical knowledge, and abnormal dependence is frequently seen. These problems raise a problem that it is difficult to interpret radiogram of the vector value map.
Moreover, in the dynamic CT image scanned by multi-slice or volume CT, a large number of arteries are further observed. This is because the same artery can be observed in a plurality of slices. If the time-density curve of the cerebral artery is prepared for all tomography images of these arteries, the number of curves becomes very large.
Furthermore, the CBP study also has the following problems. With bolus injection via the cubital vein, for a contrast enhancement effect observed with the CT, the CT number of blood rises to several hundreds of HU at maximum (several tens of HU, when contrast imaging is not performed). However, to effectively analyze the cerebral blood flow, a contrast enhancement effect has to be measured only with an error of several percentages or less. That is, even when the contrast enhancement effect (the rise of CT number) is about 20 to 40 HU, the contrast enhancement effect has to be detected.
A volume ratio of capillaries in the cerebral tissue of a unit volume is about 3 to 4% at maximum. Therefore, when the CT number of blood rises by 20 to 40 HU, a mean CT number for the cerebral tissue only rises by about 0.5 to 1.5 HU.
In the CT image, a standard deviation (sd) of noise is in inverse proportion to a square root of an X ray radiation dose, and sd is, for example, about 5 to 10 HU in typical irradiation conditions. Therefore, to detect the contrast enhancement effect of 0.5 HU, the X ray radiation dose has to be increased by about 10 to 100 times, and this means that an exposed dose of a patient is remarkably large. Moreover, since the same position is scanned several tens of times in the dynamic CT, exposure of skin in the scanned position reaches several hundreds to thousands of times the normal exposure, and this is not realistic in consideration of radiation troubles such as inflammation, alopecia, necrosis, and carcinogenesis.
Rather in the dynamic CT, the X ray radiation dose has to be decreased as compared with the usual scanning. In general, the X ray radiation dose per scan is reduced, for example, to about ½ to 1/10 of a usual dose. Thereby, about several to 20 times the X-ray exposure can only result as compared with usual one CT scanning, and any radiation trouble does not occur. However, in the CT image in which the X ray radiation dose is reduced, sd is, for example, about 15 to 20 HU, and the contrast enhancement effect of about 0.5 to 1.5 HU can hardly be detected.
Therefore, to suppress noise components of the image is one of important problems in the CBP study. For this, 1) to increase a slice thickness, 2) to average adjacent pixels, and 3) to subject the image to a smoothing processing are general measures to be taken. However, these have the following problem.
In order to “increase the slice thickness”, the slice thickness is set to be large during the scan, or the number of images of continuous thin slices is averaged and the image of a thick slice is generated. Since the X ray radiation dose per pixel increases in proportion to the slice thickness, sd of the image noise decreases in inverse proportion to the square root of the slice thickness. However, when the slice thickness is increased, a partial volume effect is produced. That is, one pixel does not show a uniform cerebral tissue, a probability that the pixel shows the mean CT number of a plurality of tissues (white matter, gray matter, blood vessel, cerebral sulci, cerebral ventricles, and the like) is incorrect, and the value of the cerebral blood flow rate obtained as the analysis result becomes incorrect.
Particularly, it is impossible to normally analyze the pixel including the influence of the vessel. Therefore, with the increased slice thickness, only a very low-quality result including a large number of pixels which cannot be analyzed is obtained.
Averaging the adjacent pixels, the spatial resolution is sacrificed to some decree. For example, a mean value of square regions (including n×n pixels) whose one side includes n pixels is obtained as a mean CT number of the whole square, this square is regarded as the pixel, and the squares are arranged to constitute a “pixel bundled image”. For example, assuming that the original image includes 512 pixels in one side (including 512×512 images), and n=2, the “pixel bundled image” is constituted of (512/2) pixels in one side (the image includes 256×256 pixels). According to the method, the noise can be reduced in inverse proportion to n. Furthermore, the number of pixels as analysis objects increases by a factor of 1/(n×n), and therefore there is an advantage that a calculation amount is also reduced.
However, when n is increased, the spatial resolution drops, and accordingly the partial volume effect occurs. That is, one pixel does not show uniform cerebral tissue, the probability that the pixel shows the mean CT number of a plurality of tissues (white matter, gray matter, blood vessel, cerebral sulci, cerebral ventricles, and the like) becomes incorrect, and the value of the cerebral blood flow rate obtained as the analysis result becomes incorrect. Particularly, it is impossible to normally analyze the pixel including the influence of the vessel. Therefore, with the increased n, the spatial resolution is low, and only the incorrect and very low-quality result including a large number of pixels which cannot be analyzed is obtained. Therefore, in practical use, n=about 2 to 4 is a limitation, and a sufficient noise suppressing effect cannot be obtained only with this measure.
Moreover, when the image is smoothed, that is, a method of operating a two-dimensional spatial filter for each CT image and smoothing the image is used, the sufficient noise suppressing effect is obtained, but the spatial resolution is remarkably impaired. Particularly, the pixel in the vicinity of a region in which thick vessels (arteries/veins) exist is influenced by the contrast enhancement effect generated in the thick vessels, and the time-density curve of these pixels is not correct. Therefore, the smoothing has to be only slightly performed. Here, in performing only the slight smoothing, it is important to remarkably reduce the size of the image filter, for example, to about 3×3. When the 3×3 smoothing filter is used to obtain a maximum image noise suppressing effect, an upper limitation is to reduce the noise sd to ⅓, and it is impossible to further suppress the noise. Therefore, a sufficient noise suppressing effect cannot be obtained.
On the other hand, when smoothing along time axis, that is, a method of regarding the time-density curve obtained for each pixel as a curve and smoothing the curve with one-dimensional filter is used, and the sufficient noise suppressing effect is obtained, the time resolution is remarkably impaired. In the CBP study, the dynamic CT is originally performed in order to obtain a high time resolution by performing scanning in a short sampling cycle and to precisely measure a slight and rapid change (degree of a smoothing effect resulting particularly from a physiologic structure) of the time-density curve, and the smoothing with time is not appropriate.